code: def get_fc_predictor_version(fc_version):
      assert fc_version in ["fp32", "fp16"], (
          "Only support fp32 and fp16 for the fully connected layer "
          "in the predictor net, the provided FC precision is {}".format(
              fc_version
          )
      )
      return fc_version
  
file_path: pytorch/caffe2/python/layers/fc.py
imports: from caffe2.python.helpers.arg_scope import get_current_scope
  from caffe2.python import schema
  from caffe2.python.layers.layers import ModelLayer
  from caffe2.python.layers.sampling_trainable_mixin import SamplingTrainableMixin
  import math
  import numpy
label_desc: Use image node_id 1 for calling a global function with example usage: get_fc_predictor_version(fc_version) and returns: fc_version